Double skin ventilated roof is one of the important passive cooling techniques that aims to reduce solar heat gain through roofs by reducing both the conduction and convection heat transfer from the roof to the ceiling of buildings. On the other hand, radiant barrier system (RBS) is very powerful in blocking the radiation heat transfer between the two skins. In this research,the effect of placing a thin layer of aluminium foil at different locations on the thermal insulation performance of a double skin ventilated roof model is investigated experimentally and the optimum location that transmits less heat flux from the lower skinis specified.The model is made of two parallel inclined galvanized steel plates. Galvanized steel has been used in the roof construction of industrial buildings and storehouses in Iraq.The radiant barrierisapplied alternately, on the outer surface of the upper skin, on the inner surface of the upper skin, suspended in the airgap between the skins, and on the inner surface of the lower skin.These casesareconsidered as Model A, Model B, Model C, and Model D, respectively. It is found that the radiant barrier can block up to78% of the heat in Model A, 71% in Model B, 94% in Model C, and 91% in Model D as compared with the Basic Model.Since the radiant barrierin both Model C and Model D blocks almost the same amount of heat, the location of the radiant barrierin Model D is chosen as the optimumradiant barrierlocation because this model is more practical.
Human interaction technology based on motion capture (MoCap) systems is a vital tool for human kinematics analysis, with applications in clinical settings, animations, and video games. We introduce a new method for analyzing and estimating dorsal spine movement using a MoCap system. The captured data by the MoCap system are processed and analyzed to estimate the motion kinematics of three primary regions; the shoulders, spine, and hips. This work contributes a non-invasive and anatomically guided framework that enables region-specific analysis of spinal motion which could be used as a clinical alternative to invasive measurement techniques. The hierarchy of our model consists of five main levels; motion capture system settings, marker data
... Show More
The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
... Show More
(1)
XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.
(10)
(8)
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show More
(23)
(23)
(5)
(3)
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show More
(33)
(24)
Background: The displacement of artificial teeth during complete denture construction presents major processing errors in the occlusal vertical dimension which were verified at the previous trial denture stage. The aim of this study was to assess the effect of delay in processing after final flask closure and tension application on the vertical acrylic and porcelain teeth displacement of complete dentures constructed from heat cured acrylic and the results were compared with the conventional processing method. Materials and methods: forty samples of identical maxillary complete dentures were constructed from heat polymerized acrylic resin. These samples were subdivided into the following experimental subgroups in which each subgroup contai
... Show More